The Full Stack Data Scientist - Python Libraries You Need To Know

Congratulations on landing your first data science job! Now, let's ensure you shine with the right tools. In this video, we'll guide you through the crucial stages of a data science project and the Python libraries you need to ace them.

From data collection with SQLAlchemy, Scrapy, Beautiful Soup, and Selenium, to exploration with NumPy, Pandas, and SciPy, we've got you covered. Discover how to manipulate data efficiently with Pandas and Polars, and handle massive datasets with PySpark and Spark SQL. Visualize your insights beautifully using Matplotlib, Seaborn, Plotly, and Streamlit. Then, dive into the model building with scikit-learn, TensorFlow, and Keras, making complex tasks a breeze.

Don't miss out on becoming a data science pro! Subscribe now for more invaluable insights and visit stratascratch.com for top-notch data science resources.

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Timeline:

Intro: (0:00)
Data Collection Libraries: (0:37)
Data Exploration Libraries: (2:01)
Data Manipulation Libraries: (3:01)
Data Visualization Libraries: (4:32)
Model Building Libraries: (5:52)
Deploying Models into Production Libraries: (7:05)
Conclusion: (3:56)

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About The Platform:

StrataScratch (https://platform.stratascratch.com/co...) is a platform that allows you to practice real data science interview questions. There are over 1000+ interview questions that cover coding (SQL and Python), statistics, probability, product sense, and business cases.

So, if you want more interview practice with real data science interview questions, visit https://platform.stratascratch.com/co.... All questions are free and you can even execute SQL and Python code in the IDE. Still, if you want to check out the solutions from other users or from the StrataScratch team, you can use ss15 for a 15% discount on the premium plans.


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